A fast iterative reconstruction algorithm of sparse angular CT based on the selective total variation.
- Author:
Huijun LI
;
Hongliang QI
;
Yuan XU
;
Linghong ZHOU
- Publication Type:Journal Article
- MeSH:
Algorithms;
Image Processing, Computer-Assisted;
Phantoms, Imaging;
Tomography, X-Ray Computed
- From:
Journal of Biomedical Engineering
2014;31(5):1011-1017
- CountryChina
- Language:Chinese
-
Abstract:
Aiming at the problem of high-quality image reconstruction from projection data at sparse angular views, we proposed an improved fast iterative reconstruction algorithm based on the minimization of selective image total variation (TV). The new reconstruction scheme consists of two components. Firstly, the algebraic reconstruction technique (ART) algorithm was adopted to reconstruct image that met the identity and non-negativity of projection data, and then, secondly, the selective TV minimization was used to modify the above image. Two phases were alternated until it met the convergence criteria. In order to further speed up the convergence of the algorithm, we applied a fast convergence technology in the iterative process. Experiments on simulated Shepp-Logan phantom were carried out. The results demonstrated that the new method not only improved image reconstruction quality and protected the edge of the image characteristics, but also improved the convergence speed of the iterative reconstruction significantly.
